Model-based fault detection and isolation system and method

ABSTRACT

A model-based Fault Detection and Isolation (FDI) system and method based on a hierarchical structure for monitoring overall vehicle system performance and diagnosing faults is disclosed. The FDI scheme uses the available sensors in a vehicle system and divides them into subsystems of smaller dimensions containing one or more modules that are related or interconnected. The same module may appear in a different subsystem, but the set of all subsystems does not have to contain all of the modules. For this structure, an FDI scheme comprising several detector units is created. Each detector unit receives information from the sensors and outputs a residual that is sent to a residual evaluation unit which processes the data and performs the residual evaluation for the selected subsystem. Finally, each subsystem outputs a decision that is sent to a supervisor unit performing the final diagnosis.

This application claims the benefit of U.S. Provisional PatentApplication No. 60/247,849 entitled FAULT DETECTION AND ISOLATION SYSTEMAND METHOD and filed Nov. 9, 2000.

TECHNICAL FIELD

The present invention is in the field of control system design. Moreparticularly, the present invention is a model-based fault detection andisolation system and method for monitoring overall system performanceand diagnosing faults. The system and method of the present inventionmay be applied to vehicle control systems.

BACKGROUND AND SUMMARY OF THE INVENTION

In recent years, increasing interest and requirement for improvedvehicle performance, reliability, and safety has focused attention onthe use of Fault Detection & Isolation (FDI) when designing vehiclecontrol systems. Fault detection and isolation is becoming one of themost important aspects in vehicle system control design. In order tomeet the increasing demand for better performance and reliability,model-based FDI schemes are being developed to address complete vehiclesystems, to detect faults in sensors and actuators, and to applyappropriate corrective action without adding new hardware to thevehicle. However, the high complexity of most vehicle systems makes thestandard FDI model-based technique difficult to apply withoutunacceptable computational effort.

The present invention is a novel system and method based on ahierarchical structure of the FDI scheme that reduces the computationaleffort of prior art systems. The FDI scheme uses the available sensorsand actuators in a system such as a vehicle system and divides them intosubsystems of smaller dimensions containing one or more modules that arerelated or interconnected. The same module may appear in a differentsubsystem, but the set of all subsystems does not have to contain all ofthe modules. For this structure, an FDI scheme comprising severaldetector units is created. Each detector unit receives information fromthe sensors and outputs a residual that is sent to a residual evaluationunit which processes the data and performs the residual evaluation forthe selected subsystem. Finally, each subsystem outputs a decision thatis sent to a supervisor unit performing the final diagnosis.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a vehicle model for an example embodimentof the present invention;

FIG. 2 is a block diagram of the general structure of a prior artmodel-based FDI method;

FIG. 3 is a block diagram of a residual generator in accordance with anexample embodiment of the present invention;

FIG. 4 is a block diagram of a hierarchical diagnostic system inaccordance with an example embodiment of the present invention;

FIG. 5 is a block diagram for the structure of a fault detector unit inaccordance with an example embodiment of the present invention;

FIG. 6 is a block diagram of a general module in accordance with anexample embodiment of the present invention;

FIG. 7 is a block diagram of a fault detection and isolation unit inaccordance with an example embodiment of the present invention;

FIG. 8 is a block diagram of the FDI scheme of the present invention;

FIG. 9 is a block diagram of the primary systems of a vehicle for anexample embodiment of the present invention;

FIG. 10 is a block diagram of the primary components for a handlingsystem for an example embodiment of the present invention;

FIG. 11 is a block diagram of the primary components for a propulsionsystem for an example embodiment of the present invention;

FIG. 12 is a block diagram of the primary components for a hybridpropulsion system for an example embodiment of the present invention;

FIG. 13 is a block diagram of the primary components for a hydraulicmachinery example embodiment of the present invention;

FIG. 14 is a graph of steering wheel angle input;

FIGS. 15-17 are graphs of estimated and actual state variables; and

FIGS. 18-23 are graphs of experimental results for a J-turn.

DETAILED DESCRIPTION OF THE INVENTION

The present invention may be implemented in accordance with softwarecomponents that provide the features and functionality described herein.The system and method of the present invention may be applied to anymachine equipped with sensors and actuators that requires reliability,safety, and availability.

Referring to FIG. 1 in an example embodiment of the present invention inwhich the system and method are applied to a vehicle control system, avehicle may be represented, in general, as a block diagram as shown inFIG. 1 constituting of two main subsystems: the core subsystem 124 andthe external subsystem. The core subsystem 124 comprises the vehicle114, tire 120, powertrain 118, steering 112, suspension 116, and brake108 modules. Each module may comprise one or more models adapted toaccept input from one or more sensors and to process input to produceone or more outputs representing aspects of the model. The vehiclemodule 114 comprises a 16DOF vehicle model. The vehicle model furthercomprises a vehicle body, (i.e., the sprung mass), and four wheels,(i.e., the unsprung masses). The model contains three translationaldegrees of freedom-longitudinal, lateral, vertical, and three rotationaldegrees of freedom-roll, pitch, and yaw for the sprung mass. Each of theunsprung masses has vertical, spin, and steering angle degrees offreedom. The tire module 120 has as inputs the longitudinal slip, thelateral slip, the vertical load, and the camber angle which gives asoutput the longitudinal and lateral force as well as aligning moment.The powertrain module 118 comprises the engine, the transmission, andthe differential models. The engine uses a lookup table with throttleposition and engine speed as inputs and gives as output the enginetorque. The transmission model inputs the engine torque and transformsthe torque based on the selected gear. The differential modelproportions the torque from the transmission to the drive wheels. Thesteering module 112 describes the elastic and geometric properties ofthe steering system. The suspension module 116 comprises the model ofthe suspension that may be of four different types: linear spring anddamper, nonlinear spring and damper, semiactive suspension, and activesuspension. The brake module 108 generates the wheel torques as afunction of the driver brake pedal force and brake controller commands.

The external subsystem comprises the environmental module 122, drivermodule 110, sensor module 100, brake controller module 102, suspensioncontroller module 104, and communication module 106. The environmentalmodule 122 determines the interfaces between the vehicle and theenvironment. The driver module 110 determines the interface between thedriver and the vehicle. This module provides information such as brakepedal force, steering angle, throttle position, and desired gear to thecore module. The sensor module 100 models the sensor dynamics. Theoutputs of this module are sent to the controller module. The brakecontroller 102 and suspension controller 104 contain algorithms used tocontrol the brake, and the suspension systems. The communication module106 models communication delays which occur in communication linksbetween controllers.

A vehicle in accordance with an example embodiment of the presentinvention may be a conventional automobile. In addition, a vehicle maybe a truck, an earth mover, a crane, a bulldozer, a tank or any otherheavy duty equipment or machinery. A vehicle may also be an airplane, aship, or a railroad car or other type of passenger or cargo transportvehicle. Any device capable of transporting persons or objects from onelocation to another in any manner may be considered a vehicle.

In the model-based FDI system and method of the present invention,analytical redundancy is used rather than physical redundancy. Thisanalytical redundancy is contained in the static and dynamicrelationship between the input and the output variables of the system.The sensitivity of a diagnostic method to modeling error is one of thekey issues in the application of model-based FDI methods. In most cases,prior art model-based FDI methods can be described by the block diagramshown in FIG. 2.

When an accurate model of the vehicle is available, the general processof the model-based FDI consists of the three stages depicted in FIG. 3.At the first stage, observations 160 acquired through sensormeasurements are compared to analytical values of the same variables ina primary residual generator 162. The error between measured andcalculated variable is called a primary residual. This residual reflectsthe system behavior, and has nominal zero mean value under normalconditions. At the second stage, the primary residuals that usuallydeviate from zero due to noise, modeling error and faults, arecommunicated to a secondary residual generator 164 and converted insecondary residuals by means of filtering, statistical testing orspectral analysis to obtain signals that can be used to analyze andisolate faults. Finally, the secondary residuals are communicated to adecision maker 166 and analyzed to isolate the fault and a diagnosis 168or decision is taken.

In accordance with the present invention, the vehicle system isdecomposed into subsystems of smaller dimension containing one or moremodules strictly related or interconnected. Referring to FIG. 4, forthis structure, the FDI scheme comprises a plurality of fault detectorunits 186, 188, 192, 194, 198, 200. Each fault detector unit 186, 188,192, 194, 198, 200 outputs a residual that is sent to a residualevaluation unit 184, 190, 196 that performs the residual evaluation forthe selected subsystem comprising the fault detector units. Finally,each subsystem that reports to a residual evaluation unit 184, 190, 196outputs a decision that is sent to a supervisor unit or fault detector182 performing the final diagnosis 180. As shown in FIG. 4, somedifferent subsystems for the vehicle are shown and each is constitutedby a residual evaluation unit 184, 190, 196 and a plurality of faultdetector units 186, 188, 192, 194, 198, 200.

The scheme for a fault detector unit 222 is depicted in FIG. 5. Eachfault detector unit 222 may comprise a plurality of models 210, 212,214, 216 and a primary residual generator 218 that sends output to aresidual evaluation unit 220.

In general, a module may be represented as in FIG. 6 where:

u_(0i), i=1 . . . m are the input vectors

Δu_(i), i=1 . . . m are the input fault vectors

θ_(0i), i=1 . . . m are the nominal parameter vectors

Δθ_(l), l=1 . . . m are the parameter fault vectors

x_(i), i=1 . . . m are the state vectors

Δy is the output fault vector

y is the output measured vector.

The module can be described by the following equations $\begin{matrix}\left\{ {\begin{matrix}{{\overset{.}{x}}_{l} = {f_{l}\quad \left( {x_{l},u_{l},\theta_{l}} \right)}} \\{y = {{h_{l}\quad \left( {x_{l},u_{l},\theta_{l}} \right)} + {\Delta \quad y}}}\end{matrix},{x_{1} \in {\Gamma_{1}\quad \vdots \quad \vdots \left\{ {\begin{matrix}{{\overset{.}{x}}_{m} = {f_{m}\quad \left( {x_{m},u_{m},\theta_{m}} \right)}} \\{y = {{h_{m}\quad \left( {x_{m},u_{m},\theta_{m}} \right)} + {\Delta \quad y}}}\end{matrix},{x_{m} \in \Gamma_{m}}} \right.}}} \right. & (1)\end{matrix}$

with u_(0i)=u_(0i)+Δu_(i), θ_(i)=θ_(0i)+Δθ_(i), i=1 . . . m, and whereΓ_(i) is a subset in which the i^(th) model equations are valid. A faultdetector unit is associated with each module. Each fault detector unitcontains a multimodel representation of the type $\begin{matrix}\left\{ {\begin{matrix}{{\hat{x}}_{l} = {g_{l}\quad \left( {{\hat{x}}_{l},u_{l},{\hat{\theta}}_{l},y} \right)}} \\{{\hat{y}}_{1} = {h_{l}\quad \left( {{\hat{x}}_{l},u_{l},{\hat{\theta}}_{l}} \right)}}\end{matrix},{{\hat{x}}_{1} \in {\Gamma_{1}\quad \vdots \quad \vdots \left\{ {\begin{matrix}{{\hat{x}}_{m} = {g_{m}\quad \left( {x_{m},u_{m},{\hat{\theta}}_{m},y} \right)}} \\{{\hat{y}}_{m} = {h_{m}\quad \left( {{\hat{x}}_{m},u_{m},{\hat{\theta}}_{m}} \right)}}\end{matrix},{{\hat{x}}_{m} \in \Gamma_{m}}} \right.}}} \right. & (2)\end{matrix}$

characterized by the fact that, without any fault, the followingconditions hold

{circumflex over (x)} _(l) →x _(l) for l→∞, i=1 . . . n  (3)

Referring to FIG. 7, each fault detector unit 222, 252, 254 comprising aplurality of models 210, 212, 214 and primary residual generator 218that generates the primary residuals 230, 240, 246 that are sent to thedecision unit 236 as shown in FIG. 7. This decision unit 236 may be acomponent of a residual evaluation unit 256 comprising secondaryresidual generators 232, 242, 248 and residual evaluators 234, 244, 250.The residual evaluations for the subsystem are performed at the residualevaluation units 234, 244, 250 and the result from the decision unit 236is sent as input to the supervisor unit 238.

The method of the FDI scheme of the present invention comprises thefollowing steps:

1. Partition of the vehicle model into subsystems containing one or moreinterconnected modules. The same module may appear in more then onesubsystem, but the set of all subsystems, in general, does not have tocontain all the modules.

2. Associate a fault detector unit to each module or smaller partitionof modules and define a multimodel representation and selection of aresidual generation method for every subsystem. The method for residualgeneration may be of different type, but commonly used approaches arethe parity space method, the observer method, and the parameteridentification method.

3. Define an appropriate residual evaluation method for each subsystem.

During operation of the vehicle, data received at the fault detectorunits is processed and passed to the appropriate residual evaluationunit. A supervisor unit receives data from the residual evaluation unitsand diagnoses problems with the vehicle.

To illustrate the method for a specific case, consider the subproblem offault detection for three important sensors:

the lateral acceleration sensor;

the steering wheel angle sensor;

the yaw rate sensor;

and for two parameters:

the front cornering stiffness; and

the rear cornering stiffness.

The structure of this example FDI scheme is shown in FIG. 8. One faultdetector unit 260 is connected to a first primary residual generator 262that connects to two residual evaluation units 264, 212. Threeadditional fault detector units 274, 276, 278 are connected to a secondprimary residual generator 280 that connects to three residualevaluation units 264, 272, 282, 284. Each residual evaluation unit 264,272, 282, 284 connects to a decision unit 268 that provides output to asupervisor unit 279.

The FDI scheme of FIG. 8 shows a fault detector unit where only onemultimodel representation for a simplified front wheel steered, smallangle, bicycle model structure is considered. The dependence of thevehicle lateral velocity and yaw rate and the longitudinal velocity onthe steering input is modeled. A simplified tire force model is adopted,whereby the lateral forces of the front and rear tires are linearlyrelated to the front and rear slip angles, through Cf and Cr the frontand rear cornering stiffness. The model is valid for nonseveremaneuvers, (i.e., for a_(iat)≦0.2 g, where g is the acceleration due togravity). The nonlinear model can be described by the equations$\begin{matrix}\left\{ \begin{matrix}{{\overset{.}{v}}_{x} = {\frac{F_{x}}{M} + {v_{y}\quad \overset{.}{\psi}}}} \\{{\overset{.}{v}}_{y} = {{{- \frac{2}{M}}\quad \left( {C_{f} + C_{r}} \right)\quad \frac{v_{y}}{v_{x}}} - {\frac{2}{M}\quad \left( {{aC}_{f} - {bC}_{r}} \right)\quad \frac{\psi}{v_{x}}} - {v_{x}\quad \overset{.}{\psi}} + {\frac{2C_{f}}{MG}\quad \delta}}} \\{\overset{¨}{\psi} = {{{- \frac{2}{7}}\quad \left( {{aC}_{f} - {bC}_{r}} \right)\quad \frac{v_{v}}{v_{x}}} - {\frac{2}{7}\quad \left( {{a^{2}\quad C_{f}} + {b^{2}\quad C_{r}}} \right)\quad \frac{\psi}{v_{x}}} + {\frac{2a\quad C_{f}}{IG}\quad \delta}}}\end{matrix} \right. & (4)\end{matrix}$

a is the distance from front wheel to C.G. of the vehicle

b is the distance from rear wheel to C.G. of the vehicle

C_(f) is the front cornering stiffness

C_(r) is the rear cornering stiffness

M is the vehicle mass

I is the vehicle moment of inertia

G is the gear ratio

F_(x) is the longitudinal force

v_(x) is the vehicle longitudinal velocity

v_(y) is the vehicle lateral velocity

δ is the steering angle

Ψ is the yaw rate

For this model, it is possible to design the following sliding modenonlinear observer based only on the yaw rate measurement$\begin{matrix}{\hat{x} = {{\left( \frac{{\partial H}\quad \left( \hat{x} \right)}{\partial\hat{x}} \right)^{- 1}\quad M\quad \left( \hat{x} \right)\quad {sign}\quad \left( {{V\quad (t)} - {H\quad \left( \hat{x} \right)}} \right)} + {B\quad \delta}}} & (5)\end{matrix}$

where

H(x)=[h₁(x) h₂(x) h₃(x)]

h₁(x)={dot over (ψ)}=r

h₂(x)={dot over (r)}

h₃(x)={umlaut over (r)}

γ(t)=[v₁(t) v₂(t) v₃(t)]

v_(i)(t)=r(t)

v_(i+1)=(m_(i)((x))sign (x(v_(i)(t)−h_(i)({circumflex over(x)}(t))))_(eq), i=1,2

M({circumflex over (x)})=diag (m₁({circumflex over (x)}) m₂({circumflexover (x)}) m₃({circumflex over (x)}))

The following table shows the error signatures.

TABLE 1 Error Signature no. fault variable cause resid. pattern 1 wheelsteering angle δ actuator failure [1 0 1 0 1 1 1] 2 lateral accela_(lat) sensor failure [1 0 1 0 1 0] 3 yaw rate r sensor failure [1 1 11 1 1] 4 Cf front cornering blow out/ incorrect inflat. [0 1 0 1 1 1]stiffness 5 Cr rear cornering blow out/ incorrect inflat. [1 1 1 1 0 1]stiffness

To simplify the problem, consider only the case of single faults. Theresidual vector is

R=[a _(iat) −â _(y1) δ−{circumflex over (δ)}a _(iat) −â _(y2) C _(f) −Ĉ_(f) a _(iat) −â _(y3) C _(r) −Ĉ _(r)]  (6)

With the choice made above, the error signature described in the Table 1may be derived.

Some simulation and experimental results obtained from the previous FDIscheme using sliding mode observers illustrate the system and method ofthe present invention. The tests are carried out for a vehicle with theparameter data set as in table 2.

TABLE 2 Parameter Values Utilized in the Steering Model. parameter valuea 1.0 [m] b 1.69 [m] Cf 60530 [N/rad] Cr 64656 [N/rad] M 1651 [Kg] I2755 [Kg/m 2] G 1 Fx 100 [N]

Although the present invention as has been described in accordance witha vehicle handling system, the present invention may be used inconjunction with types of other vehicle or machinery systems. Referringto FIG. 9, vehicles of many different types may comprise a handlingsystem 300, a propulsion system 302, and an auxiliary system 304, eachof which may comprise a plurality of modules associated with one or morefault detector units that are connected to residual evaluation units andsupervisor units. Data may be exchanged between modules in each systemto provide for optimal vehicle performance.

Referring to FIG. 10, a handling system in a vehicle may comprise abrake controller module 102, a brake module 108, a steering module 112,a driver module 110, a tire module 120, a vehicle module 114, asuspension module 116, and a suspension controller module 104. As shownin FIG. 11, modules in the handling system may communicate with modulesin the auxiliary and propulsion systems.

Referring to FIG. 11, a propulsion system in a vehicle may comprise anengine controller module 310, a fuel module 312, an air intake module314, a combustion module 316, a crank-shaft module 318, an exhaustmodule 320, and a transmission module 322. The modules in the propulsionsystem may communicate with modules in the handling and auxiliarysystems.

Referring to FIG. 12, a hybrid propulsion system may comprise aconventional propulsion system 330 as well as a supervisory controllermodule 332, a coupling module 334, an electric machine module 336, acontroller module 338, and batteries/supercapacitors 340. The modules inthe hybrid propulsion system may communicate with modules in thehandling and auxiliary systems.

Referring to FIG. 13, in a hydraulic machinery example embodiment of thepresent invention, a tank module 350, a pump module 352, a couplingmodule 354 in communication with a propulsion system 356, a controllermodule 358, a servo-valve module 360, and a cylinder module 362. Thehydraulic machinery modules may communicate with modules in the handlingand auxiliary systems.

Referring to FIG. 14, the steering input for a vehicle lane changemaneuver at a longitudinal velocity of 25-mph (11 m/s) and without anyfault is shown.

The relative state variable estimations (dashed line) are represented inFIGS. 15-17. It is possible to notice that, after a fast transient, theestimates track the true variable with a very small error.

In FIGS. 18-23, the experimental results for a Jturn at constant forwardvelocity and step change in the steering angle are presented. A steeringinput fault of 1.25 times the commanded input has been applied duringthe test. FIGS. 18 and 19 show the residuals for lateral accelerationand steering angle respectively obtained from Unit A1. In dashed lineare indicated the estimate values from the observer, a flag 0 (thresholdevaluation) may be associated to the lateral acceleration residual whilea flag 1 is associated to steering angle residual.

The residuals for lateral acceleration and front tire corneringstiffness obtained from Unit A2 are depicted in FIGS. 20 and 21 while inFIGS. 22 and 23 the lateral acceleration and the rear corneringstiffness are compared with the measured values. At the end, thefollowing residual signature is observed

R=[0 1 0 1 1 1]  (7)

which indicates a steering inputs or C_(f) fault.

The present invention supports implementation of a vehicle healthmonitor to increase the reliability of a passenger or other type ofvehicle with experimental validation of the observer design and FDIscheme. While particular embodiments of the invention have beenillustrated and described in accordance with vehicles, variousmodifications and combinations can be made without departing from thespirit and scope of the invention, and all such modifications,combinations, and equivalents are intended to be covered and claimed.

What is claimed is:
 1. A method for fault diagnosis in a transportdevice comprising the steps of: partitioning a transport device modelinto a plurality of subsystems, each subsystem comprising one or moremodules; associating a fault detector unit with each module in eachsubsystem; defining a residual evaluation method for each subsystem;evaluating data from said fault detector units in accordance with saidresidual evaluation method for each subsystem; and diagnosing a fault inaccordance with said evaluated data.
 2. The method of claim 1 whereinthe step of defining a residual evaluation method for each subsystemcomprises the step of defining a residual evaluation method selectedfrom the group consisting of parity space method, observer method, andparameter identification method.
 3. The method of claim 1 wherein thestep of partitioning a transport device model into a plurality ofsubsystems comprises the step of partitioning said transport devicemodel into a core subsystem and an external subsystem.
 4. The method ofclaim 3 wherein the core subsystem comprises a transport device dynamicsmodule, a tire module, a powertrain module, a steering module, asuspension module, and a brake module.
 5. The method of claim 3 whereinthe external subsystem comprises an environmental module, a drivermodule, a sensor module, a brake controller module, a suspensioncontroller module, and a communication module.
 6. The method of claim 3wherein said subsystem modules are selected from the group of modulesconsisting of vehicle, tire, powertrain, steering, suspension, brake,environmental, driver, sensor, brake controller, suspension controller,communication, engine controller, fuel, air intake, combustion, exhaust,crank-shaft, transmission, coupling, supervisory controller, electricmachine, controller, batteries/supercapacitors, tank, pump, servo-valve,and cylinder modules.
 7. The method of claim 3 wherein said plurality ofsubsystems comprises a handling system, a propulsion system, and anauxiliary system.
 8. A system for problem diagnosis in a transportdevice comprising: a plurality of residual evaluation units; a pluralityof fault detector units in communication with said plurality of residualevaluation units, each of said plurality of fault detector units adaptedto communicate fault data to at least one of said-residual evaluationunits; and a supervisor unit adapted to analyze evaluated data fromplurality of residual evaluation units and to diagnose a problem inaccordance with said data from said plurality of residual evaluationunits.
 9. The system of claim 8 wherein each of said residual evaluationunits evaluates fault data in accordance with a residual evaluationmethod selected from the group of evaluation methods consisting ofparity space method, observer method, and parameter identificationmethod.
 10. The system of claim 8 wherein said plurality of residualevaluation units comprises a brake/suspension/steering residualevaluation unit, a tire/vehicle dynamic residual evaluation unit, and apowertrain/driver residual evaluation unit.
 11. The system of claim 8wherein each of said plurality of fault detector units comprises aprimary residual generator adapted to generate fault data.
 12. Thesystem of claim 11 wherein said primary residual generator is adapted togenerate a primary residual representing the error between a measuredand calculated variable.
 13. The system of claim 8 wherein each of saidresidual evaluation units comprises a secondary residual generator, aresidual evaluator, and a decision unit.
 14. The system of claim 8wherein each of said plurality of fault detector units comprises a modelassociated with a module.
 15. The system of claim 14 wherein said moduleis selected from the group consisting of transport device, tire,powertrain, steering, suspension, brake, environmental, driver, sensor,brake controller, suspension controller, communication, enginecontroller, fuel, air intake, combustion, exhaust, crank-shaft,transmission, coupling, supervisory controller, electric machine,controller, batteries/supercapacitors, tank, pump, servo-valve, andcylinder modules.
 16. A transport device comprising: a first pluralityof fault detector units associated with a first module in said transportdevice adapted to output residuals for said first module; a secondplurality of fault detector units associated with a second module insaid transport device adapted to output residuals for said secondmodule; a first residual evaluation unit adapted to receive and processin accordance with a first residual evaluation method said residualsfrom said first plurality of fault detector units; a second residualevaluation unit adapted to receive and process in accordance with asecond residual evaluation method said residuals from said secondplurality of fault detector units; and a supervisor unit adapted toreceive output from said first residual evaluation unit and said secondresidual evaluation unit and to diagnose a fault in accordance with saidoutput from said first residual evaluation unit and said second residualevaluation unit.
 17. The transport device of claim 16 wherein each ofsaid fault detector units comprises a model and a primary residualgenerator adapted to generate a residual in accordance with output fromsaid model.
 18. The transport device of claim 16 wherein said firstmodule is associated with a core subsystem.
 19. The transport device ofclaim 16 wherein said second module is associated with an externalsubsystem.
 20. The transport device of claim 16 wherein said firstmodule and said second module are selected from the group of modulesconsisting of sensor, brake controller, suspension controller,communication, brake, driver, steering, transport device, suspension,powertrain, tire, environmental, engine controller, fuel, air intake,combustion, exhaust, crank-shaft, transmission, coupling, supervisorycontroller, electric machine, controller, batteries/supercapacitors,tank, pump, servo-valve, and cylinder modules.
 21. The transport deviceof claim 16 wherein each of said residual evaluation units comprises asecondary residual generator a residual evaluator, and a decision unit.22. The transport device of claim 16 wherein said first residualevaluation method and said second residual evaluation method areselected from the group of evaluation methods consisting of parity spacemethod, observer method, and parameter identification method.
 23. Thetransport device of claim 16 wherein said first module is in a handlingsystem.
 24. The transport device of claim 16 wherein said first moduleis in a propulsion system.
 25. The transport device of claim 16 whereinsaid first module is in an auxiliary system.